Hypothesis Testing and Model Selection in the Social Sciences
David L. Weakliem
Hardcovere-bookprint + e-book
Hardcover
orderApril 25, 2016
ISBN 9781462525652
Price: $65.00202 Pages
Size: 6⅛" x 9¼"
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Read the Series Editor's Note by Todd D. Little
“Weakliem offers a principled discussion of statistical methods for model selection and demonstrates them on applied problems in the social sciences. This thoughtful work should influence both statistical theory and social science practice.”
—Andrew Gelman, PhD, Department of Statistics, Columbia University
“One of the most difficult and complicated problems in any statistical analysis is model selection. In this comprehensive book, Weakliem provides a cogent and accessible presentation of existing thinking and methods. A 'must read' for any sociologist who is a serious applied quantitative researcher.”
—Christopher Winship, PhD, Diker–Tishman Professor of Sociology, Harvard University
“I especially appreciate this book's careful treatment of the philosophical arguments underlying hypothesis testing and the historical approaches that have been taken to the model selection problem. The question addressed here is not 'Which statistical test or approach should I use?' but rather, 'How can model specification, estimation, and statistical estimation advance what is known about a particular problem?' The book makes a convincing case for the utility of both traditional and Bayesian approaches—instead of calling for a Bayesian revolution—and leads quite logically to a number of ways that conventional practice can be improved. Rich bibliographies at the end of each chapter provide sources for further reading.”
—Phillip K. Wood, PhD, Department of Psychological Sciences, University of Missouri
—Andrew Gelman, PhD, Department of Statistics, Columbia University
“One of the most difficult and complicated problems in any statistical analysis is model selection. In this comprehensive book, Weakliem provides a cogent and accessible presentation of existing thinking and methods. A 'must read' for any sociologist who is a serious applied quantitative researcher.”
—Christopher Winship, PhD, Diker–Tishman Professor of Sociology, Harvard University
“I especially appreciate this book's careful treatment of the philosophical arguments underlying hypothesis testing and the historical approaches that have been taken to the model selection problem. The question addressed here is not 'Which statistical test or approach should I use?' but rather, 'How can model specification, estimation, and statistical estimation advance what is known about a particular problem?' The book makes a convincing case for the utility of both traditional and Bayesian approaches—instead of calling for a Bayesian revolution—and leads quite logically to a number of ways that conventional practice can be improved. Rich bibliographies at the end of each chapter provide sources for further reading.”
—Phillip K. Wood, PhD, Department of Psychological Sciences, University of Missouri